India NSE Volatility Index

CBOE Emerging Market Markets Volatility Index

How volatility evolves over time

How illiquidity evolves over time

{name} Model Equation

How returns affect tomorrow's volatility

How returns affect tomorrow's illiquidity

Spline Coefficients

Value at Risk (VaR) estimates the maximum loss at a given confidence level. Expected Shortfall (ES) estimates the average loss beyond VaR.

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Param	Value	t-stat
mwindow	126
αARCH	0.0668	3.50***
βGARCH	0.8913	44.41***
γleverage	0.0782	3.57***
λ₁tau intercept	7.0564	1.44
λ₂forecast adj.	0.0000	0.00
λ₃tau persistence	0.8689	4.20***

Parameter	Value	t-statistic
m window Rolling window length	126
α ARCH Response to squared shocks	0.0668	3.50***
β GARCH Volatility persistence	0.8913	44.41***
γ leverage Additional response to negative shocks	0.0782	3.57***
λ₁ tau intercept Baseline long-term coefficient	7.0564	1.44
λ₂ forecast adj. Forecast performance sensitivity	0.0000	0.00
λ₃ tau persistence Long-term factor persistence	0.8689	4.20***

V-Lab

Ashika Global Securities Ltd MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Ashika Global Securities Ltd Analyses